Sea ice surface temperature retrieval from Landsat 8/TIRS: Evaluation of five methods against in situ temperature records and MODIS IST in Arctic region

2020 ◽  
Vol 248 ◽  
pp. 111975
Author(s):  
Pei Fan ◽  
Xiaoping Pang ◽  
Xi Zhao ◽  
Mohammed Shokr ◽  
Ruibo Lei ◽  
...  
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Arctic Region ◽  
Landsat 8 ◽  
Ice Surface ◽  
Temperature Records ◽  
Ice Surface Temperature ◽  
Temperature Retrieval

scholarly journals Arctic surface temperatures from Metop AVHRR compared to in situ ocean and land data

2012 ◽  
Vol 9 (2) ◽  
pp. 1009-1043 ◽  
Author(s):  
G. Dybkjær ◽  
R. Tonboe ◽  
J. Høyer
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Temperature Data ◽  
Coupled Systems ◽  
The Arctic ◽  
In Situ Observation ◽  
Clear Sky ◽  
Ice Surface ◽  
Ice Surface Temperature

Abstract. The ice surface temperature (IST) is an important boundary condition for both atmospheric and ocean and sea ice models and for coupled systems. An operational ice surface temperature product using satellite Metop AVHRR infra-red data was developed for MyOcean. The IST can be mapped in clear sky regions using a split window algorithm specially tuned for sea ice. Clear sky conditions are prevailing during spring in the Arctic while persistent cloud cover limits data coverage during summer. The cloud covered regions are detected using the EUMETSAT cloud mask. The Metop IST compares to 2 m temperature at the Greenland ice cap Summit within STD error of 3.14 °C and to Arctic drifting buoy temperature data within STD error of 3.69 °C. A case study reveal that the in situ radiometer data versus satellite IST STD error can be much lower (0.73 °C) and that the different in situ measures complicates the validation. Differences and variability between Metop IST and in situ data are analysed and discussed. An inter-comparison of Metop IST, numerical weather prediction temperatures and in situ observation indicates large biases between the different quantities. Because of the scarcity of conventional surface temperature or surface air temperature data in the Arctic the satellite IST data with its relatively good coverage can potentially add valuable information to model analysis for the Arctic atmosphere.

scholarly journals Validation of Avhrr and Modis ice Surface temperature products using in Situ radiometers

2006 ◽  
Vol 44 ◽  
pp. 345-351 ◽  
Author(s):  
Ted A. Scambos ◽  
Terry M. Haran ◽  
Robert Massom
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Skin Temperature ◽  
Mixed Pixel ◽  
Clear Sky ◽  
Helicopter Flight ◽  
Ice Surface ◽  
Surface Skin Temperature ◽  
Ice Surface Temperature

AbstractShip-borne and airborne infrared radiometric measurements during the Arise cruise of September–October 2003 permitted in Situ validation Studies of two Satellite-based ice Surface Skin temperature algorithms: the AVHRR Polar Pathfinder Ice Surface Temperature and the MODIS Sea Ice Surface Temperature. Observations of Sea ice from the Aurora Australis Ship’s rail using a KT-19.82 radiometer were conducted between 25 September and 21 October during clear-sky overflights by AVHRR (41 passes) and MODIS (17 passes) on their respective Satellite platforms. Data from both Sensors Show highly linear fits to 1 min integrated radiometer Spot measurements, Spanning the range 245–270 K with a ±1.4˚C, 1σ (AVHRR) and ±1.0˚C (MODIS) variation relative to a 1: 1 relationship. There was no Significant offset. Helicopter observations made with a KT-19.85 radiometer on three dates (8, 19 and 20 October) provided more data (236 gridcell Sites total), but over a more limited Sea-ice Skin temperature range (252–268 K), with higher variation (±1.7˚C, 1σ) due to mixed-pixel issues. Comparison of MODIS and AVHRR algorithms directly, with both images acquired during a helicopter flight, indicates very high correlation and near-unity Slope for the two Satellite-based algorithms. Ship air-temperature data during the validation indicated moderate to Strong inversions over Sea ice under clear Skies. These formed and decayed rapidly (tens of minutes) as clouds moved out of and into the zenith area.

scholarly journals Comparison of Leads Mapping in the Arctic Ocean Between Landsat and MODIS Ice Surface Temperature Products

2019 ◽  
Vol 1 ◽  
pp. 1-1
Author(s):  
Xiaoping Pang ◽  
Pei Fan ◽  
Xi Zhao ◽  
Qing Ji
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Single Channel ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Landsat 8 ◽  
Ice Surface ◽  
Arctic Sea ◽  
Split Window Algorithm ◽  
Ice Surface Temperature

<p><strong>Abstract.</strong> Leads are linear or wedge-shaped openings in the sea ice cover. They account for about half of the sensible heat transfer from the Arctic Ocean to the atmosphere in winter, though the sea surface area covered by them is only 1%~2% of the total sea ice area, thus monitoring leads changes and mapping leads distributions become an essential role on Arctic researches. Sea ice surface temperature (IST) product from Moderate Resolution Imaging Spectroradiometer (MODIS) is the most used source of leads monitoring and mapping, however, due to the coarse spatial resolution (1km at swath level), it suffers from mixed pixel effect when describes the temperature variations on thin leads (10m~100m), thus an IST product with a finer spatial resolution is needed. Though several surface temperature retrieval algorithms had been introduced based on Landsat 8 thermal imagery, none of them were validated in Arctic sea ice region. Given that the special weather conditions such as air temperature inversion were not taken into consideration, these algorithms may not always suitable for IST acquisition in Arctic. In this paper, we applied five mainstream IST algorithms (three split window algorithms and two single channel methods) on Arctic sea ice, compared the Landsat 8 IST with corresponding MODIS IST product, and validated all the satellite ISTs by in situ temperature measurements from drifting buoys. Compared to the buoy ISTs, the single channel method through web-based atmosphere correction tool provided by Barsi et al. (2003) offers the best accuracy. The split window algorithm proposed by Du et al. (2015) ranks the second, but constrained by the banding effect due to the stripe noise. Split window algorithm introduced by Jiménez-Muñoz et al. (2014) coincides with MODIS IST product best. All of the three methods mentioned above have slightly better accuracy than MODIS IST, particular in thin leads areas, which indicated that Landsat based leads map will provide us a better insight of Arctic sea ice. All the satellite ISTs tend to underestimate the surface temperature than those measured by buoys.</p>

scholarly journals Arctic surface temperatures from Metop AVHRR compared to in situ ocean and land data

Ocean Science ◽  
2012 ◽  
Vol 8 (6) ◽  
pp. 959-970 ◽  
Author(s):  
G. Dybkjær ◽  
R. Tonboe ◽  
J. L. Høyer
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Temperature Data ◽  
Coupled Systems ◽  
The Arctic ◽  
In Situ Observation ◽  
Clear Sky ◽  
Ice Surface ◽  
Ice Surface Temperature

Abstract. The ice surface temperature (IST) is an important boundary condition for both atmospheric and ocean and sea ice models and for coupled systems. An operational ice surface temperature product using satellite Metop AVHRR infra-red data was developed for MyOcean. The IST can be mapped in clear sky regions using a split window algorithm specially tuned for sea ice. Clear sky conditions prevail during spring in the Arctic, while persistent cloud cover limits data coverage during summer. The cloud covered regions are detected using the EUMETSAT cloud mask. The Metop IST compares to 2 m temperature at the Greenland ice cap Summit within STD error of 3.14 °C and to Arctic drifting buoy temperature data within STD error of 3.69 °C. A case study reveals that the in situ radiometer data versus satellite IST STD error can be much lower (0.73 °C) and that the different in situ measurements complicate the validation. Differences and variability between Metop IST and in situ data are analysed and discussed. An inter-comparison of Metop IST, numerical weather prediction temperatures and in situ observation indicates large biases between the different quantities. Because of the scarcity of conventional surface temperature or surface air temperature data in the Arctic, the satellite IST data with its relatively good coverage can potentially add valuable information to model analysis for the Arctic atmosphere.

scholarly journals Ice Surface Temperature Retrieval from a Single Satellite Imager Band

2018 ◽  
Vol 10 (12) ◽  
pp. 1909 ◽  
Author(s):  
Yinghui Liu ◽  
Richard Dworak ◽  
Jeffrey Key
Keyword(s):  
Surface Temperature ◽  
Infrared Imaging ◽  
Single Band ◽  
Dual Band ◽  
The Arctic ◽  
Landsat 8 ◽  
Ice Surface ◽  
Window Method ◽  
Comparable Performance ◽  
Ice Surface Temperature

Current methods for estimating the surface temperature of sea and lake ice—the ice surface temperature (IST)—utilize two satellite imager thermal bands (11 and 12 μm) at moderate spatial resolution. These “split-window” or dual-band methods have been shown to have low biases and uncertainties. A single-band algorithm would be useful for satellite imagers that have only the 11 μm band at high resolution, such as the Visible Infrared Imaging Radiometer Suite (VIIRS), or that do not have a fully functional 12 μm band, such as the Thermal Infrared Sensor onboard the Landsat 8. This study presents a method for single-band IST retrievals, and validation of the retrievals using IST measurements from an airborne infrared radiation pyrometer during the NASA IceBridge campaign in the Arctic. Results show that IST with a single thermal band from the VIIRS has comparable performance to IST with the VIIRS dual-band (split-window) method, with a bias of 0.22 K and root-mean-square error of 1.03 K.

scholarly journals Deriving Arctic 2 m air temperatures over snow and ice from satellite surface temperature measurements

2021 ◽  
Author(s):  
Pia Nielsen-Englyst ◽  
Jacob L. Høyer ◽  
Kristine S. Madsen ◽  
Rasmus T. Tonboe ◽  
Gorm Dybkjær ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Arctic Region ◽  
Satellite Observations ◽  
The Arctic ◽  
Clear Sky ◽  
Ice Surface ◽  
Air Temperatures ◽  
In Situ Observations ◽  
The Arctic Region

Abstract. The Arctic region is responding heavily to climate change, and yet, the air temperature of ice covered areas in the Arctic is heavily under-sampled when it comes to in situ measurements, resulting in large uncertainties in existing weather- and reanalysis products. This paper presents a method for estimating daily mean clear sky 2 meter air temperatures (T2m) in the Arctic from satellite observations of skin temperature, using the Arctic and Antarctic ice Surface Temperatures from thermal Infrared (AASTI) satellite dataset, providing spatially detailed observations of the Arctic. The method is based on a linear regression model, which has been tuned against in situ observations to estimate daily mean T2m based on clear sky satellite ice surface skin temperatures. The daily satellite derived T2m product includes estimated uncertainties and covers clear sky snow and ice surfaces in the Arctic region during the period 2000–2009, provided on a 0.25 degree regular latitude-longitude grid. Comparisons with independent in situ measured T2m show average biases of 0.30 °C and 0.35 °C and average root mean square errors of 3.47 °C and 3.20 °C for land ice and sea ice, respectively. The associated uncertainties are verified to be very realistic for both land ice and sea ice, using in situ observations. The reconstruction provides a much better spatial coverage than the sparse in situ observations of T2m in the Arctic, is independent of numerical weather prediction model input and it therefore provides an important supplement to simulated air temperatures to be used for assimilation or global surface temperature reconstructions. A comparison between in situ T2m versus T2m derived from satellite and ERA-Interim/ERA5 estimates shows that the T2m derived from satellite observations validate similar or better than ERA-Interim/ERA5 in the Arctic.

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